DeepFrag is a deep convolutional neural network that guides ligand optimization by extending a ligand with a molecular fragment, such that the resulting extension is also highly complementary to the receptor.
An easy to use, browser-based GUI for running DeepFrag. The goal is to suggest useful chemical changes to a small-molecule ligand that might improve its binding to a protein receptor (i.e., to aid lead optimization).
FpocketWeb is a browser app for identifying pockets on protein surfaces where small-molecule ligands (e.g., drugs) might bind. It runs the fpocket executable entirely in a web browser. The pocket-finding calculations occur on the user’s computer rather than a remote server.
LigGrep is a program for identifying docked poses that participate in user-specified receptor/ligand interactions. It evaluates each docked pose and outputs the names of the compounds with poses that pass all filters.
BINANA analyzes docked ligand poses to identify molecular interactions that contribute to binding. Accurately characterizing these interactions allows medicinal chemists to assess whether a predicted ligand merits further study.
POVME2 (POcket Volume MEasurer 2) scans a molecular-dynamics simulation and extracts druggable protein pockets with unique conformations. Virtual screens that leverage these conformations often identify novel active molecules.